This document summarizes the simulation steps for investigating the performance of three multi-carrier code division multiple access (MC-CDMA) techniques: conventional MC-CDMA, orthogonal wavelet packet based MC-CDMA (WP-MC-CDMA), and Huang Hilbert Transformation (HHT) based MC-CDMA. The steps include designing the three systems, simulating them with different modulation techniques under fading channels, and comparing their bit error rate performance. Numerical and simulation results are presented to validate the proposed schemes.

1. 82
APPENDIX
The aim of this work is to investigate the performance of multi-carrier code division
multiple access (MC-CDMA) technique, which is a key technology for efficient and reliable
communication due to its high frequency spectrum efficiency and high data rate transmission. As
demand for higher data rates is continuously rising, there is always a need to develop more
efficient wireless communication systems. For this purpose, the MC-CDMA technology, which
is the combination of both orthogonal frequency division multiplexing (OFDM) and CDMA, is
considered to increase the potential benefits of the communication system.
In this thesis, we investigate the performance of conventional MC-CDMA system,
orthogonal wavelet packet based MC-CDMA system (WP-MC-CDMA), and Huang Hilbert
Transformation (HHT) based MC-CDMA system. Although, conventional MC-CDMA has
already been discussed in the literature, and used as a benchmark for other two schemes. In
addition, in the orthogonal wavelet packet based MC-CDMA system, we design a set of wavelet
packets and used as the modulation waveforms in a multicarrier CDMA system. The WP-MC-
CDMA shows their superiority over conventional MC-CDMA in terms of bit error rate (BER),
and helps to mitigate the effects of interference and channel fading. Moreover, we also
investigate the performance of Huang Hilbert Transformation based MC-CDMA. This scheme
outperforms other two techniques, because this scheme is based on the knowledge of the
instantaneous channel state information, or based on instantaneous imperfect channel estimates.
Thus, by the knowledge of their channel gains or channel information, it can analyze the data
more accurately. Hence, it is a more spectral efficient and high data rate transmission scheme
compared to the conventional MC-CDMA and WP-MC-CDMA. Furthermore, a comparison is
also made among all three schemes in terms of BER, Throughput and different modulation
techniques. Numerical and simulation results are presented to validate our proposed schemes.
Simulation Steps
Step 1: The initial phase involves review of various literatures on its basis of given MC-CDMA
and WP based MC-CDMA communication system and its process.
Step 2: The second phase consists of design the conventional MC-CDMA system and WP-MC-
CDMA system and HHT-MC-CDMA system. We have used following steps:
 Simulation of CDMA technology with fading channel.
 Simulation of conventional MC-CDMA system using MATLAB.

2. 83
 Simulation of WP-MC-CDMA system.
 Simulation for the different modulation methods like (BPSK, QPSK)
modulation technique.
 Simulation of HHT based MC-CDMA system.
 Comparative study of HHT-MC-CDMA system, WP-MC-CDMA system with
the traditional MC-CDMA system using BER and different number of users.
Step 3: Finally, the proposed method will be analyzed and compared to current methods. The
comparison will involve different parameters like BER and different number of user. The
complete methodology will be described in detail in result section.
Step 4: BER vs SNR for Conventional MC-CDMA for different users.
Step 5: BER vs SNR for Wavelet packet based MC-CDMA for dissimilar users
Step 6: BER vs SNR for HHT based MC-CDMA For Dissimilar Users
Step 7: BER vs SNR Assessment of three systems for k=1
Step 8: BER vs SNR comparisons of three System When k=2
Step 9: Performance analysis of BER using BPSK Method in MC-CDMA
Step 10: Performance analysis of BER using QPSK Technique in MC-CDMA
Step 11: Performance Analysis of BER using QAM8 Method in MC-CDMA
Step 12: Comparison Analysis of MC-CDMA using BPSK, QAM8 Modulation Techniques
Step 13: Comparative Analysis of WP MC - CDMA System using BPSK, QPSK Techniques
Step 14: Conclusion
In this thesis, the traditional MC-CDMA scheme WP-MC-CDMA as well as MC-CDMA
system based on HHT has been analyzed. In precise, we investigated how orthogonal WP based
scheme performs by scheming a group of wavelet packets. These wavelet packets were assumed
as the modulation waveforms in a MC-CDMA system. Furthermore, we examined HHT based
system. Arithmetical as well as experimental consequences demonstrate that the HHT based
System, outperforms other two in context of BER, and supports to alleviate the impact of
nosiness and channel diminishing. The upgraded performance of wavelet based system by
making use of HHT based MC-CDMA system is examined. The evaluations of BER
performance for the traditional system based on FFT, wavelet based system and HHT based
system in the diverse channel prototypes along with their evaluation for greatest realizable bit
error rate have been shown.

3. 84
Experimental outcomes were given to validate that substantial throughput, BER and
different modulation techniques like BPSK, QPSK and M Ray QAM might be realized by
presenting such grouping method having very less decoding difficulty. Consequently, the WT
based system is a practical method to reach the succeeding advancements in wireless
transmission sin tended for great information rates as well as uses. In this thesis, HHT Based
MC-CDMASystem is also evaluated. In this Paper, the diverse models of the grouping of
multiple-carrier communication with spread spectrum, specifically MC-CDMA and system
based on wavelets, as well as HHT based MC-CDMA system are comprehensively evaluated and
investigated, numerous solo-user as well as multiple-user recognition approaches and their
performance in context of bit error rate and spectral effectiveness are observed.
Step 15: MATLAB Programme
% HADAMARD MATRIX GENERATION
clc;
n=input('enter order of square hadamard matrix');
m=[];
for i=1:n
m(1,i)=-1;
end
for i=2:n
for j=1:n/2
m(i,j)=-1;
end
end
for i=2:n
for j=((n/2)+1):n
m(i,j)=1;
end
end
m
m2=[];
m2=[m m;

4. 85
m -m];
m2
% MC-CDMA USING HADAMARD CODE FOR 4 USERS%
clc ;
d = randn(1,4*100000) ;
c=1;
for o = 1:4
for j = 1:100000
if ( d(c)>=0)
D1(o,j)=1 ;
else
D1(o,j)=-1 ;
end
c = c+1 ;
end
end
for o = 1:4
j=1;
for k = 1:50000
D(o,k)=D1(o,j)+(D1(o,j+1))*1i;
j=j+2;
end
end
C=[-1 -1 -1 -1;
-1 1 -1 1;
-1 -1 1 1;
-1 1 1 -1];
M = length(C);
M

5. 86
Y = size(D);
Y
N = Y(1);
N
I = Y(2);
I
T = [];
G = zeros(I,M);
for n = 1:N
Z = zeros(I,M);
for o = 1:I
for m = 1:M
Z(o,m) = [D(n,o)*C(n,m)];
end
end
G = G + Z;
end
for o=1:I
G1(o,:)=ifft(G(o,:));
end
for snr=1:20
for o=1:I
G2(o,:)=awgn(G1(o,:),snr,0);
end
for o=1:I
G3(o,:)=fft(G2(o,:));
end
RECON = [];
for n = 1:N
TOT = zeros(1,I);

6. 87
R = zeros(I,M);
for o = 1:I
for m = 1:M
R(o,m) = G3(o,m) * C (n,m);
TOT(o) = TOT(o) + R (o,m);
end
end
RECON = [RECON ; TOT / M];
end
RECON;
RECON1=zeros(M,I);
for v = 1:M
for j = 1:I
p= real(RECON(v,j));
if (p>=0)
RECON1(v,j)=1 ;
else
RECON1(v,j)=-1 ;
end
end
end
RECON2=zeros(M,I);
for o = 1:M
for j = 1:I
p= imag(RECON(o,j));
if (p>=0)
RECON2(o,j)=1 ;
else
RECON2(o,j)=-1 ;
end
end

7. 88
end
RECON3=RECON1+(RECON2*i);
err = D-RECON3 ;
no_errs=0;
for o=1:M
for j=1:I
if(err(o,j)~=0)
no_errs=no_errs+1;
end
end
end
ber(snr)=no_errs/(I*M);
end
ber
snr=1:20
semilogy(snr,ber);
clear all
% close all
clc
t=poly2trellis(3,[6 7]); % for getting trellis structure and convolution rate is 1/2
h=seqgen.pn; % for generation of pn sequence (h is object) any other orthogonal
sequence
color='rgb';
c_ind=1;
for M=[2 4];% with different modulation
rand('state', 0);
save M M c_ind
clear all
load M
t=poly2trellis(3,[6 7]); % for getting trellis structure and convolution rate is 1/2

8. 89
%t=poly2trellis(4,[11 15]); % for getting trellis structure and convolution rate is 1/2
h=seqgen.pn; % for generation of pn sequence (h is object) any other orthogonal
sequence
color='rgb';
L = 1000*3; % length of data bit of each user
Nc = 8; % numer of chip/bit
K =[1];%number of user
user_data = randint(L,K); %initialize a matrix for user data
h.NumBitsOut=Nc; % number of pn sequence bit should be equal to number of
chip/bit(for MC CDMA)
pnstat=randint(K,6); % for K user different K states are defined each state has 6
bits?????????????????
% for convolutionally encoding the data
for i=1:K
user_coded(:,i)=convenc(user_data(:,i),t); % t is for trellis structure.
cdata3(:,:,i) = repmat(user_coded(:,i),1,Nc);
% user_coded_data1(:,i)=bin2lev(user_coded_data(:,i),M);
h.InitialStates=pnstat(i,:); % initial state is defined for each user
for kin=1:2*L % 2L because after convolutional coding user data length is double (1/2
convolution rate)????????????
pnse=generate(h); % for generating pn sequence h is defined above
% pnse_bpsk=2*pnse-1; % for converting pn sequence in bpsk (1,-1)form
spread_data(kin,:,i)=xor(cdata3(kin,:,i),pnse.'); % copier data is spreaded in frequency
domain
end
end
%spreading of data
for user=1:K

9. 90
for i=1:size(cdata3,2)
% user_coded_data(:,i)=convenc(user_data(:,i),t); % t is for trellis structure.
user_coded_data1(:,i,user)=double(bin2lev(spread_data(:,i,user),M));
end
end
DM=log(M)/log(2);
L=L/DM;
user_mod =pskmod(user_coded_data1,M); %for getting BPSK of user data
%orthogonal frequency modulation
for user=1:K
for i=1:2*L
mc_data(i,:,user)=idwt((user_mod(i,:,user)),zeros(size(user_mod(i,:,user))),'haar');% for
converting spreaded data in multicarrier CDMA data.
end
end